Online expert-based prediction for cognitive radio secondary markets.

Vanerio, Juan Martín - Larroca, Federico

Resumen:

The growing importance of wireless communications drives an increasing interest in dynamic access to spectrum resources. This requires efficient management policies that allow spectrum sharing between licensed primary users (PU) and unlicensed secondary users (SU). On such scenario, PUs shall preserve their usage priority right over any SU. Also, no SU shall interfere on any PU. Technical viability can be achieved through Cognitive Radio devices that adjust their operating parameters adaptively. After discussing several economic and technical models to achieve efficient spectrum sharing, we propose an on-demand secondary market model regulated by a spectrum broker who controls resource allocation. This model provides economic incentives for both kind of users to cooperate: SUs are charged by the broker on behalf of PUs for resource utilization but are indemnified if expelled to ensure PU priority. We describe the main characteristics of such a system and address the question of what allocation decisions should the broker take in order to achieve economic benefit regardless of users behavior. Several online expert-based no-regret algorithms are proposed to guide the decision taking process and evaluated under different user behavior patterns. Their results are compared with the ones achieved by dynamic programming to assess its convenience.

Detalles Bibliográficos
2020
Resource management
Economics
Biological system modeling
Real-time systems
Cognitive radio
Prediction algorithms
Adaptation models
Access control
Dynamic spectrum access
Decision-making
Communication system economics
Inglés
Universidad de la República
COLIBRI
https://hdl.handle.net/20.500.12008/47509
Acceso abierto
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
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author Vanerio, Juan Martín
author2 Larroca, Federico
author2_role author
author_facet Vanerio, Juan Martín
Larroca, Federico
author_role author
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collection COLIBRI
dc.contributor.filiacion.none.fl_str_mv Vanerio Juan Martín, Universidad de la República (Uruguay). Facultad de Ingeniería.
Larroca Federico, Universidad de la República (Uruguay). Facultad de Ingeniería.
dc.creator.none.fl_str_mv Vanerio, Juan Martín
Larroca, Federico
dc.date.accessioned.none.fl_str_mv 2024-12-12T14:58:25Z
dc.date.available.none.fl_str_mv 2024-12-12T14:58:25Z
dc.date.issued.none.fl_str_mv 2020
dc.description.abstract.none.fl_txt_mv The growing importance of wireless communications drives an increasing interest in dynamic access to spectrum resources. This requires efficient management policies that allow spectrum sharing between licensed primary users (PU) and unlicensed secondary users (SU). On such scenario, PUs shall preserve their usage priority right over any SU. Also, no SU shall interfere on any PU. Technical viability can be achieved through Cognitive Radio devices that adjust their operating parameters adaptively. After discussing several economic and technical models to achieve efficient spectrum sharing, we propose an on-demand secondary market model regulated by a spectrum broker who controls resource allocation. This model provides economic incentives for both kind of users to cooperate: SUs are charged by the broker on behalf of PUs for resource utilization but are indemnified if expelled to ensure PU priority. We describe the main characteristics of such a system and address the question of what allocation decisions should the broker take in order to achieve economic benefit regardless of users behavior. Several online expert-based no-regret algorithms are proposed to guide the decision taking process and evaluated under different user behavior patterns. Their results are compared with the ones achieved by dynamic programming to assess its convenience.
dc.format.extent.es.fl_str_mv 12 p.
dc.format.mimetype.es.fl_str_mv application/pdf
dc.identifier.citation.es.fl_str_mv Vanerio, J. y Larroca, F. "Online expert-based prediction for cognitive radio secondary markets". IEEE Transactions on Cognitive Communications and Networking. [en línea]. 2020, vol. 6, no. 1, pp. 340-351.
dc.identifier.issn.none.fl_str_mv 2332-7731
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12008/47509
dc.language.iso.none.fl_str_mv en
eng
dc.publisher.es.fl_str_mv IEEE
dc.relation.none.fl_str_mv IEEE Transactions on Cognitive Communications and Networking, vol. 6, no. 1, mar 2020, pp. 340-351.
dc.rights.license.none.fl_str_mv Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
dc.source.none.fl_str_mv reponame:COLIBRI
instname:Universidad de la República
instacron:Universidad de la República
dc.subject.es.fl_str_mv Resource management
Economics
Biological system modeling
Real-time systems
Cognitive radio
Prediction algorithms
Adaptation models
Access control
Dynamic spectrum access
Decision-making
Communication system economics
dc.title.none.fl_str_mv Online expert-based prediction for cognitive radio secondary markets.
dc.type.es.fl_str_mv Artículo
dc.type.none.fl_str_mv info:eu-repo/semantics/article
dc.type.version.none.fl_str_mv info:eu-repo/semantics/publishedVersion
description The growing importance of wireless communications drives an increasing interest in dynamic access to spectrum resources. This requires efficient management policies that allow spectrum sharing between licensed primary users (PU) and unlicensed secondary users (SU). On such scenario, PUs shall preserve their usage priority right over any SU. Also, no SU shall interfere on any PU. Technical viability can be achieved through Cognitive Radio devices that adjust their operating parameters adaptively. After discussing several economic and technical models to achieve efficient spectrum sharing, we propose an on-demand secondary market model regulated by a spectrum broker who controls resource allocation. This model provides economic incentives for both kind of users to cooperate: SUs are charged by the broker on behalf of PUs for resource utilization but are indemnified if expelled to ensure PU priority. We describe the main characteristics of such a system and address the question of what allocation decisions should the broker take in order to achieve economic benefit regardless of users behavior. Several online expert-based no-regret algorithms are proposed to guide the decision taking process and evaluated under different user behavior patterns. Their results are compared with the ones achieved by dynamic programming to assess its convenience.
eu_rights_str_mv openAccess
format article
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identifier_str_mv Vanerio, J. y Larroca, F. "Online expert-based prediction for cognitive radio secondary markets". IEEE Transactions on Cognitive Communications and Networking. [en línea]. 2020, vol. 6, no. 1, pp. 340-351.
2332-7731
instacron_str Universidad de la República
institution Universidad de la República
instname_str Universidad de la República
language eng
language_invalid_str_mv en
network_acronym_str COLIBRI
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oai_identifier_str oai:colibri.udelar.edu.uy:20.500.12008/47509
publishDate 2020
reponame_str COLIBRI
repository.mail.fl_str_mv karina.camps@seciu.edu.uy
repository.name.fl_str_mv COLIBRI - Universidad de la República
repository_id_str 4771
rights_invalid_str_mv Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
spelling Vanerio Juan Martín, Universidad de la República (Uruguay). Facultad de Ingeniería.Larroca Federico, Universidad de la República (Uruguay). Facultad de Ingeniería.2024-12-12T14:58:25Z2024-12-12T14:58:25Z2020Vanerio, J. y Larroca, F. "Online expert-based prediction for cognitive radio secondary markets". IEEE Transactions on Cognitive Communications and Networking. [en línea]. 2020, vol. 6, no. 1, pp. 340-351.2332-7731https://hdl.handle.net/20.500.12008/47509The growing importance of wireless communications drives an increasing interest in dynamic access to spectrum resources. This requires efficient management policies that allow spectrum sharing between licensed primary users (PU) and unlicensed secondary users (SU). On such scenario, PUs shall preserve their usage priority right over any SU. Also, no SU shall interfere on any PU. Technical viability can be achieved through Cognitive Radio devices that adjust their operating parameters adaptively. After discussing several economic and technical models to achieve efficient spectrum sharing, we propose an on-demand secondary market model regulated by a spectrum broker who controls resource allocation. This model provides economic incentives for both kind of users to cooperate: SUs are charged by the broker on behalf of PUs for resource utilization but are indemnified if expelled to ensure PU priority. We describe the main characteristics of such a system and address the question of what allocation decisions should the broker take in order to achieve economic benefit regardless of users behavior. Several online expert-based no-regret algorithms are proposed to guide the decision taking process and evaluated under different user behavior patterns. Their results are compared with the ones achieved by dynamic programming to assess its convenience.Submitted by Ribeiro Jorge (jribeiro@fing.edu.uy) on 2024-12-09T22:25:08Z No. of bitstreams: 2 license_rdf: 25790 bytes, checksum: 13adb202270a5f7cee03e795b33133c4 (MD5) VL20.pdf: 374123 bytes, checksum: e871f9c7662c1f6ff9df5d94f8f25a7e (MD5)Approved for entry into archive by Machado Jimena (jmachado@fing.edu.uy) on 2024-12-12T12:54:46Z (GMT) No. of bitstreams: 2 license_rdf: 25790 bytes, checksum: 13adb202270a5f7cee03e795b33133c4 (MD5) VL20.pdf: 374123 bytes, checksum: e871f9c7662c1f6ff9df5d94f8f25a7e (MD5)Made available in DSpace by Luna Fabiana (fabiana.luna@seciu.edu.uy) on 2024-12-12T14:58:25Z (GMT). No. of bitstreams: 2 license_rdf: 25790 bytes, checksum: 13adb202270a5f7cee03e795b33133c4 (MD5) VL20.pdf: 374123 bytes, checksum: e871f9c7662c1f6ff9df5d94f8f25a7e (MD5) Previous issue date: 202012 p.application/pdfenengIEEEIEEE Transactions on Cognitive Communications and Networking, vol. 6, no. 1, mar 2020, pp. 340-351.Las obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad de la República.(Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)info:eu-repo/semantics/openAccessLicencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)Resource managementEconomicsBiological system modelingReal-time systemsCognitive radioPrediction algorithmsAdaptation modelsAccess controlDynamic spectrum accessDecision-makingCommunication system economicsOnline expert-based prediction for cognitive radio secondary markets.Artículoinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionreponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaVanerio, Juan MartínLarroca, FedericoTelecomunicacionesAnálisis de Redes, Tráficos y Estadísticas de Servicios (ARTES)LICENSElicense.txtlicense.txttext/plain; charset=utf-84267http://localhost:8080/xmlui/bitstream/20.500.12008/47509/5/license.txt6429389a7df7277b72b7924fdc7d47a9MD55CC-LICENSElicense_urllicense_urltext/plain; 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spellingShingle Online expert-based prediction for cognitive radio secondary markets.
Vanerio, Juan Martín
Resource management
Economics
Biological system modeling
Real-time systems
Cognitive radio
Prediction algorithms
Adaptation models
Access control
Dynamic spectrum access
Decision-making
Communication system economics
status_str publishedVersion
title Online expert-based prediction for cognitive radio secondary markets.
title_full Online expert-based prediction for cognitive radio secondary markets.
title_fullStr Online expert-based prediction for cognitive radio secondary markets.
title_full_unstemmed Online expert-based prediction for cognitive radio secondary markets.
title_short Online expert-based prediction for cognitive radio secondary markets.
title_sort Online expert-based prediction for cognitive radio secondary markets.
topic Resource management
Economics
Biological system modeling
Real-time systems
Cognitive radio
Prediction algorithms
Adaptation models
Access control
Dynamic spectrum access
Decision-making
Communication system economics
url https://hdl.handle.net/20.500.12008/47509